Sequencing of Polyclonal Antibodies by Integrating Intact Mass, Middle–Down, and De Novo Bottom–Up Mass Spectrometry
peer-reviewed · Molecular & Cellular Proteomics · 2025
| Date | 2025-11-01 |
| Type | peer-reviewed |
| Venue | Molecular & Cellular Proteomics |
| Publisher | Elsevier BV |
| Contribution | downstream-application |
| DOI | 10.1016/j.mcpro.2025.101088 |
| Citations (OpenAlex) | 3 |
| Venue 2-year citedness | 4.69 |
Abstract
Polyclonal antibodies (pAbs) represent nature’s approach to robust immunity, targeting multiple sites on pathogens, but their complex mixtures have remained largely unsequenceable, limiting their therapeutic potential. While monoclonal antibodies (mAbs) dominate therapeutics because of their reproducibility, pAbs offer superior resilience against viral mutations and broader target recognition. Current pAb sequencing attempts have shown limitations, requiring germline databases or B-cell sequencing. Due to the highly variable nature of antibodies, as well as the possibility of unavailable B cells, there is a need for a purely mass spectrometry- and de novo sequencing-based solution. Here, we present PolySeq.AI, an automated de novo workflow that combines bottom-up, middle-down, and intact mass analysis, to accurately sequence pAb samples without relying on external databases. PolySeq.AI achieved >99% sequencing accuracy across all tested samples, including an mAb mixture from the HB-95 cell line and a mixture of four mAbs, with complete bottom-up coverage and strong middle-down fragment support. Importantly, recombinant antibodies produced from our de novo sequences of HB-95 antibodies retained full binding capabilities to human leukocyte antigen-I complexes, confirming the accuracy and efficacy of our pAb de novo sequencing workflow.
Methods and tools
- PolySeq.AI: An automated workflow that integrates de novo bottom-up, middle-down and intact mass spectrometry to sequence polyclonal antibody mixtures without germline databases or B-cell sequencing, validated by expressing recombinant antibodies.
Methods it uses
- ALPS: Assembles de novo sequenced peptides and their per-residue confidence scores into a de Bruijn graph to reconstruct complete monoclonal antibody heavy and light chains without a template.
Data deposited
Cites (13)
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